메뉴 건너뛰기




Volumn 21, Issue 7, 2008, Pages 721-726

An application of supervised and unsupervised learning approaches to telecommunications fraud detection

Author keywords

Fraud detection; Supervised learning; Telecommunications; Unsupervised learning; User profiling

Indexed keywords

COMPUTER NETWORKS; LEARNING ALGORITHMS; UNSUPERVISED LEARNING;

EID: 51149102669     PISSN: 09507051     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.knosys.2008.03.026     Document Type: Article
Times cited : (78)

References (32)
  • 1
    • 51149101916 scopus 로고    scopus 로고
    • ACTS ACo95, project ASPeCT: legal aspects of fraud detection, AC095/KUL/W26/DS/P/25/2, 1998.
    • ACTS ACo95, project ASPeCT: legal aspects of fraud detection, AC095/KUL/W26/DS/P/25/2, 1998.
  • 2
    • 51149090231 scopus 로고    scopus 로고
    • G. Adomavicious, Al. Tuzhilin, User profiling in personalization applications through rule discovery and validation, in: Proc. ACM SIGKDD-99, ACM Press, San Diego, CA, USA, 1999, pp. 377-381.
    • G. Adomavicious, Al. Tuzhilin, User profiling in personalization applications through rule discovery and validation, in: Proc. ACM SIGKDD-99, ACM Press, San Diego, CA, USA, 1999, pp. 377-381.
  • 3
    • 51149119803 scopus 로고    scopus 로고
    • R. Alves et al., Discovering telecom fraud situations through mining anomalous behavior patterns, in: KDD 2006 Workshop on Data Mining for Business Applications, Philadelphia, USA, 2006.
    • R. Alves et al., Discovering telecom fraud situations through mining anomalous behavior patterns, in: KDD 2006 Workshop on Data Mining for Business Applications, Philadelphia, USA, 2006.
  • 4
    • 84255186507 scopus 로고    scopus 로고
    • R. Buschkes, D. Kesdogan, P. Reichl, How to increase security in mobile networks by anomaly detection, in: Proc. 14th Annual Computer Security Applications Conference - ACSAC'98, 1998, p. 8.
    • R. Buschkes, D. Kesdogan, P. Reichl, How to increase security in mobile networks by anomaly detection, in: Proc. 14th Annual Computer Security Applications Conference - ACSAC'98, 1998, p. 8.
  • 6
    • 85131711070 scopus 로고    scopus 로고
    • T.J. Downey, D.J. Meyer, R.K. Price, E.L. Spitznagel, Using the receiver operating characteristic to asses the performance of neural classifiers, in: Int. Joint Conf. Neural Networks, vol. 5, 1999, pp. 3642-3646.
    • T.J. Downey, D.J. Meyer, R.K. Price, E.L. Spitznagel, Using the receiver operating characteristic to asses the performance of neural classifiers, in: Int. Joint Conf. Neural Networks, vol. 5, 1999, pp. 3642-3646.
  • 8
    • 51149123747 scopus 로고    scopus 로고
    • T. Fawcett, C. Phua, Fraud Detection Bibliography (2005). Available from: .
    • T. Fawcett, C. Phua, Fraud Detection Bibliography (2005). Available from: .
  • 9
    • 51149099319 scopus 로고    scopus 로고
    • (accessed 26.07.07).
    • (accessed 26.07.07).
  • 10
    • 51149121952 scopus 로고    scopus 로고
    • P. Gosset, M. Hyland, Classification, detection and prosecution of fraud in mobile networks, in: Proc. ACTS Mobile Summit, Sorrento, Italy, 1999.
    • P. Gosset, M. Hyland, Classification, detection and prosecution of fraud in mobile networks, in: Proc. ACTS Mobile Summit, Sorrento, Italy, 1999.
  • 13
    • 51149091076 scopus 로고    scopus 로고
    • C.S. Hilas, J.N. Sahalos, User profiling for fraud detection in telecommunications networks, in: Proc. 5th Int. Conf. Technology and Automation - ICTA'05, Thessaloniki Greece, 2005, pp. 382-387.
    • C.S. Hilas, J.N. Sahalos, User profiling for fraud detection in telecommunications networks, in: Proc. 5th Int. Conf. Technology and Automation - ICTA'05, Thessaloniki Greece, 2005, pp. 382-387.
  • 14
    • 33749825000 scopus 로고    scopus 로고
    • Testing the fraud detection ability of different user profiles by means of FF-NN classifiers
    • Kollias S., et al. (Ed), Springer-Verlag, Berlin Heidelberg
    • Hilas C., and Sahalos J. Testing the fraud detection ability of different user profiles by means of FF-NN classifiers. In: Kollias S., et al. (Ed). ICANN 2006, Part II, LNCS 4132 (2006), Springer-Verlag, Berlin Heidelberg 872-883
    • (2006) ICANN 2006, Part II, LNCS , vol.4132 , pp. 872-883
    • Hilas, C.1    Sahalos, J.2
  • 15
    • 51149119378 scopus 로고    scopus 로고
    • S.F. Hinde, Call Record Analysis. Making Life Easier - Network Design and Management Tools (Digest No: 1996/217), IEE Colloquium on, (1996) 8/1-8/4 20.
    • S.F. Hinde, Call Record Analysis. Making Life Easier - Network Design and Management Tools (Digest No: 1996/217), IEE Colloquium on, (1996) 8/1-8/4 20.
  • 16
  • 17
    • 0142080708 scopus 로고    scopus 로고
    • J. Hollmen, V. Tresp, Call-based fraud detection in mobile communication networks using a hierarchical regime switching model, in: Proc. 1998 Conf. Advances in Neural Information Processing Systems II, MIT Press, 1999, pp. 889-895.
    • J. Hollmen, V. Tresp, Call-based fraud detection in mobile communication networks using a hierarchical regime switching model, in: Proc. 1998 Conf. Advances in Neural Information Processing Systems II, MIT Press, 1999, pp. 889-895.
  • 20
    • 18844459283 scopus 로고    scopus 로고
    • Potential fraudulent usage in mobile telecommunications networks
    • Lin Y.-B., Chen M., and Rao H. Potential fraudulent usage in mobile telecommunications networks. IEEE Transactions on Mobile Computing 1 2 (2002) 123-131
    • (2002) IEEE Transactions on Mobile Computing , vol.1 , Issue.2 , pp. 123-131
    • Lin, Y.-B.1    Chen, M.2    Rao, H.3
  • 21
    • 0036804085 scopus 로고    scopus 로고
    • Network intrusion and fault detection: a statistical anomaly approach
    • Manikopoulos C., and Papavassilliou S. Network intrusion and fault detection: a statistical anomaly approach. IEEE Communications Magazine 40 10 (2002) 76-82
    • (2002) IEEE Communications Magazine , vol.40 , Issue.10 , pp. 76-82
    • Manikopoulos, C.1    Papavassilliou, S.2
  • 23
    • 51149090229 scopus 로고    scopus 로고
    • Matlab release 13, User Manual, The Math Works Inc., 2002.
    • Matlab release 13, User Manual, The Math Works Inc., 2002.
  • 24
    • 51149112786 scopus 로고    scopus 로고
    • Y. Moreau, B. Preneel, P. Burge, J. Shawe-Taylor, C. Stoermann, C. Cooke, Novel techniques for fraud detection in mobile telecommunication networks, in: Proc. ACTS Mobile Summit, Granada, Spain, 1997.
    • Y. Moreau, B. Preneel, P. Burge, J. Shawe-Taylor, C. Stoermann, C. Cooke, Novel techniques for fraud detection in mobile telecommunication networks, in: Proc. ACTS Mobile Summit, Granada, Spain, 1997.
  • 25
    • 51149093772 scopus 로고    scopus 로고
    • Y. Moreau, J. Vandewalle, Detection of mobile phone fraud using supervised neural networks: a first prototype, in: Proc. Int. Conf. Artificial Neural Networks - ICANN'97, 1997, pp. 1065-1070.
    • Y. Moreau, J. Vandewalle, Detection of mobile phone fraud using supervised neural networks: a first prototype, in: Proc. Int. Conf. Artificial Neural Networks - ICANN'97, 1997, pp. 1065-1070.
  • 26
    • 51149097614 scopus 로고    scopus 로고
    • M. Nagano, B. Kermanshahi, Temperature forecasting using artificial neural networks, in: Proc. ICEE, Kitakyushu, Japan, 2000.
    • M. Nagano, B. Kermanshahi, Temperature forecasting using artificial neural networks, in: Proc. ICEE, Kitakyushu, Japan, 2000.
  • 27
    • 0242468747 scopus 로고    scopus 로고
    • An anomaly intrusion detection method by clustering normal user behavior
    • Oh S.H., and Lee W.S. An anomaly intrusion detection method by clustering normal user behavior. Computers & Security 22 7 (2003) 596-612
    • (2003) Computers & Security , vol.22 , Issue.7 , pp. 596-612
    • Oh, S.H.1    Lee, W.S.2
  • 28
    • 29144443664 scopus 로고    scopus 로고
    • Minority report in fraud detection: classification of skewed data
    • Phua C., Alahakoon D., and Lee V. Minority report in fraud detection: classification of skewed data. ACM SIGKDD Explorations 6 1 (2004) 50-58
    • (2004) ACM SIGKDD Explorations , vol.6 , Issue.1 , pp. 50-58
    • Phua, C.1    Alahakoon, D.2    Lee, V.3
  • 29
    • 84943274699 scopus 로고    scopus 로고
    • M. Riedmiller, H. Braun, A direct adaptive method for faster backpropagation learning: the RPROP algorithm, in: Proc. IEEE Int. Conf. Neural Networks 1, 1993, pp. 586-591.
    • M. Riedmiller, H. Braun, A direct adaptive method for faster backpropagation learning: the RPROP algorithm, in: Proc. IEEE Int. Conf. Neural Networks 1, 1993, pp. 586-591.
  • 30
    • 51149119799 scopus 로고    scopus 로고
    • S. Rosset, U. Murad, E. Neumann, Y. Idan, G. Pinkas, Discovery of fraud rules for telecommunications - challenges and solutions, in: Proc. ACM SIGKDD-99, ACM Press, San Diego, CA, USA, 1999, pp. 409-413.
    • S. Rosset, U. Murad, E. Neumann, Y. Idan, G. Pinkas, Discovery of fraud rules for telecommunications - challenges and solutions, in: Proc. ACM SIGKDD-99, ACM Press, San Diego, CA, USA, 1999, pp. 409-413.
  • 32
    • 84892142402 scopus 로고    scopus 로고
    • M. Taniguchi, M. Haft, J. Hollmen, V. Tresp, Fraud detection in communication networks using neural and probabilistic methods, in: Proc. 1998 IEEE Int. Conf. Acoustics, Speech and Signal Processing, vol. 2, 1998, pp. 1241-1244.
    • M. Taniguchi, M. Haft, J. Hollmen, V. Tresp, Fraud detection in communication networks using neural and probabilistic methods, in: Proc. 1998 IEEE Int. Conf. Acoustics, Speech and Signal Processing, vol. 2, 1998, pp. 1241-1244.


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.